NDLI: Soluble Solids Content and pH Prediction and Maturity Discrimination of Lychee Fruits Using Visible and Near Infrared Hyperspectral Imaging

Content Provider	Springer Nature Link
Author	Pu, Hongbin Liu, Dan Wang, Lu Sun, Da Wen
Copyright Year	2015
Abstract	Hyperspectral imaging (HSI) technique has shown promise as a rapid and nondestructive tool to evaluate various internal quality attributes of fruits and vegetables. The objective of this study was to investigate the nondestructive prediction of soluble solids content (SSC) and pH of lychees and maturity discrimination. Two hyperspectral imaging systems of visible/short-wave near infrared range (600–1000 nm, Spectral Set I) and long-wave near infrared range (1000–2500 nm, Spectral Set II) were employed. Results showed that Spectral Set II (SSC: r $_{ p }$ = 0.877, RMSEP = 0.911 °Brix; pH: r $_{ p }$ = 0.745, RMSEP = 0.291) performed better than Spectral Set I (SSC: r $_{ p }$ = 0.790, RMSEP = 1.279 °Brix; pH: r $_{ p }$ = 0.701, RMSEP = 0.308) for the internal quality prediction of litchi and maturity discrimination. The partial least square discriminant analysis (PSL-DA) model had a discrimination rate of 90.63 % for Spectral Set I and 96.88 % for Spectral Set II. β-Coefficients of partial least squares regression (PLSR) models were used to choose optimal wavelengths for quality predictions. The performance of optimized PLSR in both spectral sets were comparable to the models developed using the whole spectral range.
Starting Page	235
Ending Page	244
Page Count	10
File Format	PDF
ISSN	19369751
Journal	Food Analytical Methods
Volume Number	9
Issue Number	1
e-ISSN	1936976X
Language	English
Publisher	Springer US
Publisher Date	2015-05-10
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Nondestructive Hyperspectral imaging Lychee Maturity discrimination Soluble solids content pH Food Science Chemistry/Food Science Microbiology Analytical Chemistry
Content Type	Text
Resource Type	Article
Subject	Analytical Chemistry Safety Research Safety, Risk, Reliability and Quality Applied Microbiology and Biotechnology Food Science

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